• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.78-81
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• 2004

As a society has Progressed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized externally and internally. However, in the process of digitalization or transmission of data, noise is generated by several causes, and researches for eliminating those noises have been continued until now. The mean filter is useful method to remove AWGN (additive white gaussian noise) from degraded image and has excellent low-frequency properties. However, it brings about degradation of high-frequency properties in image. So in this paper we removed noise with mean filters added directional information and minimized degradation of high-frequency properties.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.38-48
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• 2011

Block based LCD backlight nonideality and crosstalk compensation methodologies are proposed based on the analysis of backlight profiles and image pixel homogeneity. Large computation complexity required in the conventional compensations is minimized without the degradation of image qualities by optimizing image block size, image area inside the block to be excluded from the compensation computation and the required backlight range to be computed. The optimization results of computation complexity as well as image qualities are verified for the proposed compensation by real image data simulations.

• Current Optics and Photonics
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• v.7 no.3
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• pp.237-247
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• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.1
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• pp.20-25
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• 2013

Ultrasonic methods are widely used to degradation assessment. Remaining-life cycle of metal can be estimated by ultrasonic parameters because ultrasonic velocity and attenuation are affected by change of material properties with accumulated fatigue in the metal. Therefore, in this study, we will estimate overall change of material properties by 2D C-scan image. Fatigued aluminum alloy 6061-T6 samples from 0 to 85% were prepared for evaluating fatigue life cycle. Also, degraded image of materials using attenuation is proposed to estimate degree of material degradation for determining degraded area of fatigued samples. Finally, we will predicts process pf degradation with measured attenuation of fatigued aluminum alloy 6061-T6 samples.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.48-53
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• 1991

The discrete cosine transform (DCT)-based progressive and hierarchical coding schemes developed by the International Standardization Organization (ISO) Joint Photographic Experts Groups (JPEG) are implemented and evaluated for the application of medical image communication. For a series of head sections of magnetic resonance images, a compression ratio of about 10 is obtained by the algorithm without noticeable image degradation.

• Journal of the Korean Chemical Society
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• v.56 no.4
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• pp.484-490
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• 2012

The tin (IV) oxide nanoparticles are prepared by controlled precipitation method and calcined at temperatures of $200-600^{\circ}C$. The prepared $SnO_2$ nanoparticles characterized by XRD patterns, TEM image, IR and UV-Vis spectra. The XRD patterns and TEM image show the tetragonal structure and spherical morphology for $SnO_2$ nanoparticles, respectively. The photocatalytic activity of the prepared $SnO_2$ nanoparticles studied in degradation reaction of methylene blue (MB). The results show the size of nanoparticles, band-gap energy and photocatalytic activity of $SnO_2$ depends on the calcinations temperature. The $SnO_2$ nanoparticles calcined at $500^{\circ}C$ indicated the highest photoreactivity. Also, the zero-valent tin (ZVT) nanoparticles with tetragonal structure are prepared by a reducing agent and used as a catalyst in degradation of MB. In basic pH of 11, the degradation >95% of MB at time 150 min obtained at presence of ZVT nanoparticles.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.168-174
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• 2017

Videos recorded on surveillance cameras or by car black boxes at night have distorted images due to illumination variation. Therefore, it is difficult to analyze morphological characteristics of objects, and it is limiting to use such distorted images as evidence in traffic accidents. Image restoration is performed by amplifying the brightness of nighttime images using linearized gamma correction to increase their contrast (which destroys visual information) and by minimizing degradation factors caused by irregular traveling.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.858-869
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• 2023

As one of the pivotal techniques of image restoration, single-channel blind source separation (SCBSS) is capable of converting a visual-only image into multi-source images. However, image degradation often results from multiple mixing methods. Therefore, this paper introduces an innovative SCBSS algorithm to effectively separate source images from a composite image in various mixed modes. The cornerstone of this approach is a novel triple generative adversarial network (TriGAN), designed based on dual learning principles. The TriGAN redefines the discriminator's function to optimize the separation process. Extensive experiments have demonstrated the algorithm's capability to distinctly separate source images from a composite image in diverse mixed modes and to facilitate effective image restoration. The effectiveness of the proposed method is quantitatively supported by achieving an average peak signal-to-noise ratio exceeding 30 dB, and the average structural similarity index surpassing 0.95 across multiple datasets.

• Journal of the Optical Society of Korea
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• v.5 no.1
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• pp.9-15
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• 2001

The ocean Scanning Multi-spectral Imager (OSMI) is a payload on the KOrea Multi-Purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring f the study of biological oceanography. OSMI performs solar and dark calibrations for on-orbit instrument calibration. The purpose of the solar calibration is to monitor the degradation of imaging performance for each pixel of 6 spectral bands and to correct the degradation effect on OSMI image during the ground station date processing. The design, the operation concept, and the radiometric characteristics of the solar calibration are investigated. A linear model of image response and a solar calibration radiance model are proposed to study the instrument characteristics using the solar calibration data. The performance of spectral responsivity and spatial response uniformity. The first solar calibration data and the analysis results are important references for further study on the on-orbit stability of OSMI response during its lifetime.